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dc.contributor.author Guðjónsson, Ásmundur Alma
dc.contributor.author Loftsson, Hrafn
dc.contributor.author Daðason, Jón Friðrik
dc.date.accessioned 2021-06-10T12:38:13Z
dc.date.available 2021-06-10T12:38:13Z
dc.date.issued 2021
dc.identifier.uri http://hdl.handle.net/20.500.12537/118
dc.description A dockerized Named Entity Recognition (NER) API for Icelandic. It uses a ELECTRA-base language model, that has been fine tuned for NER using MIM-GOLD-NER. It achieves F1-score of ~91.9 on the test set for MIM-GOLD-NER. The code for the API is available at https://github.com/cadia-lvl/Icelandic-NER-API and the files for the fine tuned model are available in this submission. Dockerútfærð forritaskil fyrir nafnakennsl (NER) á íslensku. Það notast við ELECTRA-base mállíkan, sem hefur verið fínstillt fyrir NER með nafnakennslamálheildinni MIM-GOLD-NER. Líkanið nær u.þ.b. 91.9 fyrir prófunarmengi MIM-GOLDöNER. Forritunarkóðinn fyrir forritaskilinu eru aðgengileg hérna: https://github.com/cadia-lvl/Icelandic-NER-API og skrárnar fyrir fínstillta líkanið má finna í þessari færslu.
dc.language.iso isl
dc.publisher Reykjavík University
dc.rights The MIT License (MIT)
dc.rights.uri https://opensource.org/licenses/mit-license.php
dc.rights.label PUB
dc.source.uri https://github.com/cadia-lvl/Icelandic-NER-API/releases/tag/1.0
dc.subject named entity recognition
dc.subject transformer
dc.subject webservice
dc.subject api
dc.title Icelandic NER API - ELECTRA-base model (21.05)
dc.type toolService
metashare.ResourceInfo#ContentInfo.detailedType tool
metashare.ResourceInfo#ResourceComponentType#ToolServiceInfo.languageDependent true
has.files yes
branding Clarin IS Repository
demo.uri https://electra-ner-icelandic-gwafmrdfha-ez.a.run.app/
contact.person Ásmundur Alma Guðjónsson asmundur10@ru.is Reykjavik University
sponsor Ministry of Education Science and Culture Support tools: Named Entity Recognition (I7) Language Technology for Icelandic 2019-2023 nationalFunds
files.size 408675628
files.count 1


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ELECTRA-base-trained-NER.zip
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trained model files
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  • model
    • pytorch_model.bin420 MB
    • tokenizer_config.json438 B
    • test_results.txt366 B
    • config.json1 kB
    • training_args.bin2 kB
    • vocab.txt253 kB
    • special_tokens_map.json112 B
    • eval_results.txt380 B
    • test_predictions.txt904 kB

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